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Deepak Dass

Open to work0 years experience

Full Stack Developer

New Delhi, IndiaTarget Roles: Backend Engineer • Full-Stack Developer • Frontend Specialist

Full Stack Developer specializing in React.js, Node.js, and AI/LLM integration.

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Standing Rank

Rank Not Available

Developer Badges

Badges Pending

Skills & Technologies

44 skills
javascripttypescripthtml5css3pythonc++react.jsredux toolkittailwind cssframer motionvitereact router domscssnode.jsexpress.jsrest api designjwtbcryptmulterbullmqredisexpress-rate-limitgoogle gemini apigroq sdkcoheremistral airagmulti-llm routingprompt engineeringmongodb atlasmongoosefirebase authfirestoremysqlgitgithubpostmanvercelrendernetlifyci/cdcloudinaryimagekityoutube data api v3

Work Experience

Full Stack Developer

Zeenik Solution

May 2024 - Oct 2024 New Delhi
  • Architected a Blog Platform using React.js, Tailwind CSS, and Firebase with Role-Based Access Control (RBAC), Admin and User panels, and real-time database listeners — scaled to support 100 or more concurrent users with zero downtime.
  • Boosted mobile engagement by 20 percent and achieved a 95 plus Google Lighthouse performance score by implementing lazy loading, code splitting, and responsive design optimizations.
  • Cut codebase duplication by 35 percent by designing a reusable React component library, reducing average feature delivery time and improving maintainability across the team.

Projects

Memora — AI-Powered Knowledge Management System

View Project
React 18Node.jsExpressMongoDBBullMQRedisGeminiCohereMistral
  • Engineered a multi-LLM routing engine using Gemini 2.5 Flash, Cohere, and Mistral dispatched via asynchronous BullMQ and Redis queues, enabling fully non-blocking background AI processing for auto-tagging, summarization, and semantic embedding across articles, videos, and PDFs.
  • Constructed a Knowledge Graph with an optimized tag-index algorithm delivering 5x faster relationship mapping compared to the naive nested-loop approach, and an Omni-Search querying three parallel sources (personal library, YouTube Data API, and DuckDuckGo) concurrently in under 50 milliseconds.
  • Introduced a RAG pipeline for context-aware note retrieval, embedding user-saved content into Gemini vector space and surfacing semantically relevant chunks to ground LLM responses in personal knowledge.
  • Applied six targeted performance optimizations including compound database indexes, Gzip compression middleware, and in-memory authentication caching with a 30-second TTL, reducing API payload size by 80 percent and redundant database reads by 80 percent.

AI Interview Preparation Platform

View Project
React 19Vite 7Tailwind CSS v4Node.jsExpress 5MongoDBGroq SDKLLaMA 3.3-70BJWT
  • Developed an end-to-end AI interview prep platform generating role-specific question-and-answer sets via LLaMA 3.3-70B through the Groq SDK, with session persistence, a Concept Deep Dive sidebar for on-demand explanations, and dynamic question expansion without data loss.
  • Secured the application with JSON Web Token authentication, bcrypt password hashing, protected route middleware, and file upload handling; rendered AI responses with Markdown and code syntax highlighting, producing a production-quality developer experience.
  • Implemented pin-and-unpin mechanics and session-based progress tracking, enabling users to prioritize key questions and resume preparation sessions without losing state between visits.

DEALMIND AI — Real-Time Negotiation Simulator

View Project
React 19Tailwind CSS v4Framer MotionRedux ToolkitNode.jsExpressMongoDBGoogle Gemini API
  • Built a Gemini-powered negotiation simulation game featuring three distinct AI seller personalities (Logical, Impatient, and Cautious), real-time Trust and Patience meters, and automatic session termination on tactical missteps — creating measurable win-or-loss outcomes per round.
  • Designed five negotiation tactics (Offer, Justify, Rapport, Bluff, and Walk Away), each backed by a unique prompt engineering strategy, and managed all global game state via Redux Toolkit to enforce a single source of truth and eliminate state-related defects.
  • Integrated AI-generated post-game debrief using the Gemini API, delivering personalized feedback on negotiation strategy and decision quality at the conclusion of every completed session.

Leaderboard Standings

Leaderboard Position Pending

Global test scores, peer standing percentiles, and algorithm leaderboard ranks are updated dynamically.

Assessment Highlights

Assessments Not Completed

Coding evaluations, system assessment results, and conceptual score badges will appear here after taking a test.

AI Collaboration Score

AI Collaboration Score Pending

Developer coding behavior, assistant cooperation, and AI pair-programming indicators are evaluated during live coding sessions.

Role Compatibility Profile

Role Compatibility Analysis Pending

Custom matching reports, candidate role compatibility percentiles, and core engineer strength profiles are processed once conceptual code screenings are complete.

Achievements

Achievements Not Earned

Special rewards, developer badges, system recognition certificates, and conceptual milestones will display here.

About Details

Professional Bio

Full Stack Developer with expertise in React.js, Node.js, and AI integration. Experienced in building scalable web applications, optimizing performance, and implementing RAG pipelines and multi-LLM routing engines.

Bachelor of Computer Applications (BCA)

Chandigarh University, Mohali (2022 - 2025)

Languages: English, Hindi
Email: Locked